most citedA Review of Modern Recommender Systems Using Generative Models (Gen-RecSys)

3 citations · 3 across the 5 of their papers we have counts for

collaborators

7 papers

cs.MA2026

See What I See, Know What I Think: Dense Latent Communication Across Heterogeneous Agents

Siyi Chen, Xiaoyan Zhang, Meng Wu +7

Language-model agents build internal representations of the information they observe and the reasoning they perform. Sharing these representations offers a way to communicate both…

cs.LG2026

Dictionary-Aligned Concept Control for Safeguarding Multimodal LLMs

Jinqi Luo, Jinyu Yang, Tal Neiman +5

Multimodal Large Language Models (MLLMs) have been shown to be vulnerable to malicious queries that can elicit unsafe responses. Recent work uses prompt engineering, response class…

cs.LG2026

Reliable and Responsible Foundation Models: A Comprehensive Survey

Xinyu Yang, Junlin Han, Rishi Bommasani +49

Foundation models, including Large Language Models (LLMs), Multimodal Large Language Models (MLLMs), Image Generative Models (i.e, Text-to-Image Models and Image-Editing Models), a…

cs.IR2024

Recommendation with Generative Models

Yashar Deldjoo, Zhankui He, Julian McAuley +8

Generative models are a class of AI models capable of creating new instances of data by learning and sampling from their statistical distributions. In recent years, these models ha…

cs.IR2024

Multi-modal Generative Models in Recommendation System

Arnau Ramisa, Rene Vidal, Yashar Deldjoo +8

Many recommendation systems limit user inputs to text strings or behavior signals such as clicks and purchases, and system outputs to a list of products sorted by relevance. With t…

cs.AI2024

Large Language Model Driven Recommendation

Anton Korikov, Scott Sanner, Yashar Deldjoo +8

While previous chapters focused on recommendation systems (RSs) based on standardized, non-verbal user feedback such as purchases, views, and clicks -- the advent of LLMs has unloc…

cs.IR2024★ 3 cited

A Review of Modern Recommender Systems Using Generative Models (Gen-RecSys)

Yashar Deldjoo, Zhankui He, Julian McAuley +7

Traditional recommender systems (RS) typically use user-item rating histories as their main data source. However, deep generative models now have the capability to model and sample…